The NetSys Lab

The NetSys Lab

Welcome to the homepage of the NetSys (Networked Systems) lab at Stony Brook University. Our lab works on problems in the intersection of networking and systems, with a current focus on smartphones and wearable devices.

 

Research

Sustainable NLP

Making NLP models run efficiently both on small form factor devices and on data centers, to improve power consumption and latency.

SBUWear

Using wearable devices to improve the accessibility and usability of smartphone applications.

Webgaze

Improving the "perceptual" performance of Web page loads by leveraging user's eye gaze.

WProfX

Significantly improving mobile page load performance by studying the fundamental bottlenecks in the mobile page load process.

News

  • February 2020: Congratulations to Dr Jian Xu and Dr Yi Cao on their successful defense. Jian is off to Oracle and Yi has joined ByteDance

  • Janurary 2020: Conor's work from IBM Research on using deep learning for Web cryptomining detection accepted at MADWeb 2020, colocated with NDSS 2020.

  • September 2019: Three papers accepted at IMC. One (long) paper on rethinking TCP modeling, one (short) paper on BBR performance bottlenecks, and one (short) paper on characterizing JSON traffic, which is fast becoming a more dominant traffic in CDNs compared to HTML. Congratulations to Yi Cao and Santiago Vargas who led the works.

  • July 2019: DarkReader paper that makes smartphones more power efficient for blind users accepted at ASSETS (SIGACCESS Conference on Computers and Accessibility). The paper is also nominated for a best paper award! Congratulations to Syed and Jian.

  • March 2019: We designed a reading detector that can detect when a user is reading a Web page versus skimming. This work is accepted at ETRA 2019 and is part of our ongoing work on understanding user engagement on Web pages. Congratulations to Conor!  

  • Mar 2019: DeQA accepted to MobiSys'19

  • Oct 2018: Aruna recieves the VMWare Early Career Grant and is selected as one of the N²Women Rising Stars in Computer Networking and Communications.